Exploration on the correlation of economic complexity and air quality

doi:10.3969/j.issn.1004-9479.2023.07.2021176

Abstract

Abstract:

Economic complexity, as a new indicator to measure the quality of regional economic development, has attracted more and more attention in recent years. The relationship between economic complexity and environmental quality is one of the key topics to discuss. However, those studies were mainly based on the experience of developed countries, with insufficient attention to inside mechanisms and applicability in developing countries. Therefore, this paper utilized data from the China Customs Database and the Ministry of Ecology and Environment in 2005 and 2016 to describe the evolution of economic complexity and air quality in Chinese cities, and constructed an econometric model to explore their relationship as well as potential mechanism. The results show that: ①Economic complexity is positively related to air quality, suggesting that higher economic complexity leads to better air quality; ②Green technology has a positive effect on local air quality, and economic complexity can enhance this green technological effect; ③Industrial pollution structure is a key factor causing air pollution, but an increase of economic complexity can offset the negative impact from polluting industry to a certain extent; ④The environmental effects of different factors have obvious regional heterogeneity, suggesting that environmental governance measures in different regions should focus on different aspects.

Key words: economic complexity, air quality, green technology, industrial pollution structure, green development

摘要：

近年来，经济复杂度作为衡量地区经济发展水平的新指标愈发受到学者关注，其中该指标与环境质量的关系是重点讨论话题之一。然而，现有研究主要基于发达国家经验，对其关系机制和在发展中国家、转型经济体适用性的关注仍存在不足。利用2005—2016年中国海关数据库与国家生态环境部网站等数据，描述中国地级市经济复杂度与空气质量的格局演化，构建计量模型探究中国城市经济复杂度与空气质量的关联性，并分析经济复杂度环境效应的潜在机制。结果表明：①经济复杂度与空气质量呈正向关联，城市经济复杂度越高则空气质量越好；②绿色技术对地方空气质量改善存在积极作用，且经济复杂度可以增强绿色技术的改善效应；③产业污染结构是造成空气污染的重要原因之一，但经济复杂度的提升能一定程度上抵消污染产业对空气质量的负面影响；④各因素对空气质量的作用存在明显的区域异质性，不同地区的环境治理手段应有不同侧重。

关键词: 经济复杂度, 空气质量, 绿色技术, 产业污染结构, 绿色发展

Huizhen TANG, Zhuoran REN, Canfei HE. Exploration on the correlation of economic complexity and air quality[J]. World Regional Studies, 2023, 32(7): 88-101.

汤慧桢, 任卓然, 贺灿飞. 城市经济复杂度与空气质量的关联性探究[J]. 世界地理研究, 2023, 32(7): 88-101.

Figures/Tables 9

References 39

1	蔺雪芹, 王岱. 中国城市空气质量时空演化特征及社会经济驱动力. 地理学报, 2016, 71(08): 1357-1371.
	LIN X, WANG D. Spatiotemporal evolution of urban air quality and socioeconomic driving forces in China. Journal of Geographical Sciences, 2016, 71(08): 1357-1371.
2	HIDALGO C A, HAUSMANN R. The building blocks of economic complexity. Proceedings of the National Academy of Sciences of the United States of America, 2009, 106(26): 10570-10575.
3	MEALY P, TEYTELBOYM A. Economic complexity and the green economy. Research Policy, 2022, 51(8):103948.
4	CAN M, GÖZGÖR G. The impact of economic complexity on carbon emissions: Evidence from France. Environmental Science & Pollution Research International, 2017, 24(10): 16364-16370.
5	YILANCI V, PATA U K. Investigating the EKC hypothesis for China: the role of economic complexity on ecological footprint. Environmental Science and Pollution Research, 2020, 27(2), 32683-32694.
6	GAO J, ZHOU T. Quantifying China's regional economic complexity. Physica A-Statistical Mechanics and Its Applications, 2018(492): 1591-1603.
7	LEVINSON A. Technology, trade international, and from U.S. manufacturing pollution. The American Economic Review, 2009, 99(5): 2177-2192.
8	HAUSMANN R, HIDALGO C A, BUSTOS S, et al. The Atlas of Economic Complexity: Mapping Paths to Prosperity. Cambridge, MA:MIT Press, 2014.
9	HAUSMANN R, KLINGER B. The structure of the product space and the evolution of comparative advantage: CID working papers from center for international development No.146(2007-04-23)[2020-04-30]..
10	HIDALGO C A, KLINGER B, BARABASI A, et al. The product space conditions the development of nations. Science, 2007, 317(5837): 482-487.
11	HAUSMANN R, HIDALGO C A. Country diversification, product ubiquity, and economic divergence. Social Science Electronic Publishing, 2010, 69(35): 78-81.
12	HARTMANN D, GUEVARA M, JARAFIGUEROA C, et al. Linking economic complexity, institutions and income inequality. World Development, 2017(93): 75-93.
13	NEAGU O. The link between economic complexity and carbon emissions in the European Union countries: a model based on the Environmental Kuznets Curve (EKC) Approach. Sustainability, 2019, 11(17): 4753.
14	NEAGU O, TEODORU M C. The relationship between economic complexity, energy consumption structure and greenhouse gas emission: heterogeneous panel evidence from the EU countries. Sustainability, 2019, 11(2): 497.
15	TACCHELLA A, CRISTELLI M, CALDARELLI G, et al. A new metrics for countries' fitness and products' complexity. Scientific Reports, 2012(2): 723.
16	ALBEAIK S, KALTENBERG M, ALSALEH M, et al. Improving the economic complexity index: arXiv.org. (2017-07-) [2020-04-30]. .
17	MORRISON G, BULDYREV S V, IMBRUNO M, et al. On economic complexity and the fitness of nations. Scientific Reports, 2017, 7(1): 1-11.
18	SWART J, BRINKMANN L. Economic complexity and the environment: evidence from Brazil. // FILHO W L, TORTATO U, FRANKENBERGER F. Universities and Sustainable Communities: Meeting the Goals of the Agenda 2030. Switzerland: ChamSpringer, 2020.
19	BOLETI E, GARAS A, KYRIAKOU A, et al. Economic complexity and environmental performance: Evidence from a world sample. Environmental Modeling & Assessment, 2021(26):251-270.
20	ABDON A, BACATE M L, FELIPE J, et al. Product complexity and economic development. Structural change and economic dynamics, 2012, 23(1): 36-68.
21	BISHOP A, MATEOSGARCIA J. Exploring the link between economic complexity and emergent economic activities. National Institute Economic Review, 2019, 249(1): 47-58.
22	MAO X, HE C. Export upgrading and environmental performance: Evidence from China. Geoforum, 2017(86): 150-159.
23	张崇辉,苏为华,曾守桢.基于CHME理论的环境规制水平测度研究.中国人口·资源与环境, 2013, 23(1):19-24.
	ZHANG C, SU W, ZENG S. Environmental regulation measure research based on CHME theory. China Population, Resources and Environment, 2013, 23(1):19-24.
24	GROSSMAN G M, KRUEGER A B. Economic growth and the environment. Quarterly Journal of Economics, 1995, 110(2): 353-377.
25	贺灿飞,周沂,张腾. 中国产业转移及其环境效应研究.城市与环境研究, 2014, 1(1):34-49.
	HE C, ZHOU Y, ZHANG T. Industrial transfer and its environmental effect in China. Urban and Environmental Studies, 2014, 1(1):34-49.
26	王俊松, 贺灿飞. 技术进步、结构变动与中国能源利用效率. 中国人口·资源与环境, 2009, 19(2): 157-161.
	WANG J, HE C. Technological development, structural change and Chinese energy consumption efficiency. China Population, Resources and Environment, 2009, 19(2): 157-161.
27	林永生, 马洪立. 大气污染治理中的规模效应、结构效应与技术效应——以中国工业废气为例. 北京师范大学学报(社会科学版), 2013(3): 129-136.
	LIN Y, MA H. Scale, structural, and technique effect in air pollution abatement: Taking China's industrial waste gas as example. Journal of Beijing Normal University(Social Sciences), 2013,(3): 129-136.
28	成艾华.技术进步、结构调整与中国工业减排——基于环境效应分解模型的分析. 中国人口·资源与环境, 2011, 21(3): 41-47.
	CHENG A. Technological progress, structural readjustment and pollution reduction for the industry in China. China Population, Resources and Environment, 2011, 21(3): 41-47.
29	原毅军, 谢荣辉. 产业集聚、技术创新与环境污染的内在联系. 科学学研究, 2015, 33(09): 1340-1347. .
	YUAN Y, XIE R. Empirical research on the relationship of industrial agglomeration, technological innovation and environmental pollution. Studies in Science of Science, 2015,33(09): 1340-1347.
30	GRETHER J, MATHYS N A, de MELO J. Scale, technique and composition effects in manufacturing SO₂ emissions. Environmental and Resource Economics, 2009, 43(2): 257-274.
31	李振发, 贺灿飞, 黎斌. 中国出口产品地区专业化. 地理科学进展, 2018, 37(7): 963-975.
	LI Z, HE C, LI B. Regional specialization of China's export products. Progress in Geography, 2018, 37(7): 963-975.
32	李稚, 段珅, 孙涛. 制造业产业集聚如何影响生态环境——基于绿色技术创新与外商直接投资的双中介模型. 科技进步与对策, 2019, 36(6): 51-57.
	LI Z, DUAN K, SUN T. How does industrial agglomeration of manufacturing industry affect ecological environment? --Research on dual mediation model based on green technology innovation and foreign direct investment. Science & Technology Progress and Policy, 2019, 36(6): 51-57.
33	刘云强, 权泉, 朱佳玲, 等. 绿色技术创新、产业集聚与生态效率——以长江经济带城市群为例. 长江流域资源与环境, 2018, 27(11): 2395-2406.
	LIU Y, QUAN Q, ZHU J, et al. Green technology innovation, industrial agglomeration and ecological efficiency--A case study of urban agglomerations on Yangtze River Economic Belt. Resources and Environment in the Yangtze Basin, 2018, 27(11): 2395-2406.
34	肖悦. 中国空气质量时空分布特征及影响因素分析. 重庆: 西南大学, 2018.
	XIAO Y. Spatiotemporal pattern of air quality and its influencing factors in China. Chongqing: Southwest University, 2018.
35	潘圆圆, 唐健. 中国高污染产业的出口与环境管制差异关系初探. 国际经贸探索, 2011, 27(3): 4-9.
	PAN Y, TANG J. The relationship of Chinese high-pollution exports and environmental regulations. International Economics and Trade Research, 2011, 27(3): 4-9.
36	薛海, 张帆. 降水量与城市大气环境关系——以113个环保重点城市为例. 自然资源学报, 2020, 35(4): 937-949.
	XUE H, ZHANG F. Study on the relationship between precipitation and urban atmospheric environment: Cases of 113 key environmental protection cities. Journal of Natural Resources, 2020, 35(4): 937-949.
37	周兆媛, 张时煌, 高庆先, 等.京津冀地区气象要素对空气质量的影响及未来变化趋势分析. 资源科学, 2014, 36(1): 191-199.
	ZHOU Z, ZHANG S, GAO Q, et al. The impact of meteorological factors on air quality in the Beijing-Tianjin-Hebei Region and trend analysis. Resources Science, 2014, 36(1): 191-199.
38	王志平, 陶长琪, 沈鹏熠. 基于生态足迹的区域绿色技术效率及其影响因素研究. 中国人口·资源与环境, 2014, 24(1): 35-40.
	WANG Z, TAO C, SHEN P. Regional green technical efficiency with its influencing factors analysis based on ecological footprint. China Population, Resources and Environment, 2014, 24(1): 35-40.
39	周沂, 贺灿飞, 刘颖. 中国污染密集型产业地理分布研究. 自然资源学报, 2015, 30(7): 1183-1196.
	ZHOU Y, HE C, LIU Y. An empirical study on the geographical distribution of pollution-intensive industries in China. Journal of Natural Resources, 2015, 30(7): 1183-1196.

对应中国行业类别	SITC1代码
金属矿床开采	281、283
初级有色金属	681、682、683、684、685、686、687、689
纸浆与纸	251、641、642
初级钢铁	671、672、673、674、675、676、678
化学制品	512、513、514、581

对应中国行业类别	SITC1代码
金属矿床开采	281、283
初级有色金属	681、682、683、684、685、686、687、689
纸浆与纸	251、641、642
初级钢铁	671、672、673、674、675、676、678
化学制品	512、513、514、581

变量	主效应			非线性	调节效应
变量	模型1	模型2	模型3	模型4	模型5	模型6
ECI⁺	－0.47^***	－0.54^***	－0.59^***	－1.23^***	－0.75^***	－0.59^***
	(－3.30)	(－3.59)	(－3.90)	(－5.81)	(－4.22)	(－3.89)
ECI⁺ 2				－0.02^***
				(－4.29)
lnPolluper		1.05^***	1.14^***	1.16^***	1.10^***	1.04^***
		(－2.92)	(－3.16)	(－3.24)	(－3.06)	(－2.77)
lnGreentec			－2.00^***	－2.67^***	－2.26^***	－2.02^***
			(－2.77)	(－3.63)	(－3.06)	(－2.79)
ECI⁺_Greentec					－0.09^*
					(－1.72)
ECI⁺_Polluper						－0.041
						(－0.87)
lnGDP	－9.33^***	－9.30^***	－6.05^**	－7.15^**	－6.19^**	－6.08^**
	(－3.68)	(－3.65)	(－2.16)	(－2.56)	(－2.21)	(－2.17)
lnAsset	3.01^**	3.21^**	3.48^**	3.59^**	3.58^**	3.51^**
	(－2.03)	(－2.14)	(－2.33)	(－2.42)	(－2.39)	(－2.35)
lnRegu	－0.94^**	－1.04^**	－0.88^**	－0.97^**	－0.93^**	－0.86^*
	(－2.15)	(－2.35)	(－1.97)	(－2.19)	(－2.07)	(－1.93)
lnRain	－0.13	－0.15	－0.14	－0.12	－0.14	－0.14
	(－0.59)	(－0.67)	(－0.64)	(－0.56)	(－0.61)	(－0.62)
lnTempr	0.32	0.32	0.39	0.39	0.39	0.39
	(－0.59)	(－0.58)	(－0.71)	(－0.72)	(－0.70)	(－0.70)
lnHumidity	－0.45	－0.48	－0.51	－0.51	－0.50	－0.50
	(－0.71)	(－0.77)	(－0.81)	(－0.82)	(－0.81)	(－0.81)
Constant	141.97^***	138.35^***	108.04^***	124.50^***	110.60^***	107.96^***
	(－12.74)	(－12.05)	(－6.82)	(－7.69)	(－6.96)	(－6.81)
Observations	1 399	1 383	1 383	1 383	1 383	1 383
Number of id	285	283	283	283	283	283
固定效应	YES	YES	YES	YES	YES	YES

变量	主效应			非线性	调节效应
变量	模型1	模型2	模型3	模型4	模型5	模型6
ECI⁺	－0.47^***	－0.54^***	－0.59^***	－1.23^***	－0.75^***	－0.59^***
	(－3.30)	(－3.59)	(－3.90)	(－5.81)	(－4.22)	(－3.89)
ECI⁺ 2				－0.02^***
				(－4.29)
lnPolluper		1.05^***	1.14^***	1.16^***	1.10^***	1.04^***
		(－2.92)	(－3.16)	(－3.24)	(－3.06)	(－2.77)
lnGreentec			－2.00^***	－2.67^***	－2.26^***	－2.02^***
			(－2.77)	(－3.63)	(－3.06)	(－2.79)
ECI⁺_Greentec					－0.09^*
					(－1.72)
ECI⁺_Polluper						－0.041
						(－0.87)
lnGDP	－9.33^***	－9.30^***	－6.05^**	－7.15^**	－6.19^**	－6.08^**
	(－3.68)	(－3.65)	(－2.16)	(－2.56)	(－2.21)	(－2.17)
lnAsset	3.01^**	3.21^**	3.48^**	3.59^**	3.58^**	3.51^**
	(－2.03)	(－2.14)	(－2.33)	(－2.42)	(－2.39)	(－2.35)
lnRegu	－0.94^**	－1.04^**	－0.88^**	－0.97^**	－0.93^**	－0.86^*
	(－2.15)	(－2.35)	(－1.97)	(－2.19)	(－2.07)	(－1.93)
lnRain	－0.13	－0.15	－0.14	－0.12	－0.14	－0.14
	(－0.59)	(－0.67)	(－0.64)	(－0.56)	(－0.61)	(－0.62)
lnTempr	0.32	0.32	0.39	0.39	0.39	0.39
	(－0.59)	(－0.58)	(－0.71)	(－0.72)	(－0.70)	(－0.70)
lnHumidity	－0.45	－0.48	－0.51	－0.51	－0.50	－0.50
	(－0.71)	(－0.77)	(－0.81)	(－0.82)	(－0.81)	(－0.81)
Constant	141.97^***	138.35^***	108.04^***	124.50^***	110.60^***	107.96^***
	(－12.74)	(－12.05)	(－6.82)	(－7.69)	(－6.96)	(－6.81)
Observations	1 399	1 383	1 383	1 383	1 383	1 383
Number of id	285	283	283	283	283	283
固定效应	YES	YES	YES	YES	YES	YES

百分位	断裂点
1%	－33.48
5%	－4.51
50%	3.45
95%	9.68
99%	12.88